Quantitative Fluorescence Imaging-Guided Detection and Targeted Therapy Monitoring Platform for Ovarian Cancer Micrometastases

卵巢癌微转移定量荧光成像引导检测及靶向治疗监测平台

• 批准号: 10058694
• 负责人: Ulas Sunar
• 金额: $ 34.09万
• 依托单位: WRIGHT STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10058694
• 关键词: Acids; Address; Adjuvant Chemotherapy; Algorithms; Antineoplastic Agents; Biodistribution; Biopsy; Cancer Patient; Cell Culture Techniques; Cell Line; Clinic; Clinical; Combination Drug Therapy; Data; Detection; Diagnosis; Disease; Dose; Doxorubicin; Drug Targeting; Ensure; Epithelial; Epithelial ovarian cancer; Epithelium; Excision; Exposure to; FOLR1 gene; Feedback; Fluorescence; Folic Acid; Goals; Image; Imaging technology; In Vitro; Kinetics; Laparoscopes; Lead; Lesion; Light; Lighting; Lipids; Liposomal Doxorubicin; Liposomes; Malignant Neoplasms; Malignant neoplasm of gastrointestinal tract; Malignant neoplasm of lung; Malignant neoplasm of ovary; Maps; Metastatic Malignant Neoplasm to the Ovary; Micrometastasis; Microscopic; Modality; Monitor; Neoplasm Metastasis; Nodule; Normal tissue morphology; Operative Surgical Procedures; Ovarian; Ovarian Carcinoma; PUVA Photochemotherapy; Patients; Pharmaceutical Preparations; Phospholipids; Photosensitization; Photosensitizing Agents; Phototherapy; Physiological; Platinum; Porphyrins; Protocols documentation; Public Health; Quality of life; Recurrence; Resistance; Resolution; Scheme; Sensitivity and Specificity; Shapes; Signal Transduction; Spatial Frequency Domain Imaging; Structure; Surface; Survival Rate; System; Technology; Therapeutic; Time; Tissues; Toxic effect; Translating; Treatment Efficacy; Visualization; absorption; anti-cancer; attenuation; base; cancer cell; cancer diagnosis; cancer therapy; chemotherapy; contrast enhanced; controlled release; deep learning; deep learning algorithm; fluorescence imaging; image guided; image guided therapy; image-guided drug delivery; imaging approach; imaging modality; imaging platform; improved; in vivo; intraperitoneal; liposome vector; malignant mouth neoplasm; nano; nanocarrier; nanomedicine; novel; optical imaging; phantom model; quantitative imaging; side effect; spatiotemporal; targeted treatment; treatment optimization; tumor; tumor specificity; uptake

PROJECT SUMMARY/ABSTRACT A major challenge in the management of advanced ovarian cancer is the presence of disseminated microscopic tumor nodules within the intraperitoneal cavity. Despite surgery and adjuvant chemotherapy, as many as 50% of patients can show occult disseminated disease, with only a 43% survival rate. Furthermore, systemic chemotherapy can have toxic side effects. Thus, recent efforts have aimed at improving detection and treatment of micromets. Chemophototherapy (CPT), the combination of chemotherapy and photodynamic therapy, is an emerging cancer treatment modality that can provide synergistic efficacy of both therapies. The overall goal is to implement a quantitative laparoscopic imaging and treatment approach for advanced detection of micromets and optimization of CPT for targeted destruction of ovarian micromets and reduced toxic side effects. Quantitative fluorescence laparoscopic imaging will provide high sensitivity and resolution for detecting micromets as well as image guided drug delivery. Folate receptor alpha (FA) will be used as a promising target because it is highly specific of epithelial ovarian cancer. The proposed targeted CPT compound has a ~6-fold tumor-specificity providing enhanced fluorescence contrast. These folate-targeted, porphyrin-phospholipid doped liposomes are triggered directly by near infrared (NIR) light. This activates the anti-cancer photosensitizer outer layer and releases the anti-cancer agent Doxorubicin (Dox). While this nanocarrier is expected to improve detection of micromets, tissue absorption and scattering in living tissue can confound fluorescence contrast. Quantitative imaging based on spatial frequency domain imaging can eliminate these confounding effects and provide quantitative contrasts to enable more sensitive detection compared to raw fluorescence or white light visualization. Furthermore, this quantitative capability can function in near-real-time to provide feedback on drug release, thus allowing image-guided optimization of treatment light to ensure full drug release within each tumor. In Aim 1, a wide-field dual-channel laparoscope, fast quantification algorithms and targeted liposomal nano-construct will be implemented and optimized. In Aim 2, the platform will be validated in vivo for improved detection of micromets vs. raw fluorescence and white light. In Aim 3, the platform’s efficacy will be validated in vivo for destroying micromets in targeted tumors while reducing toxicity to surrounding normal tissues. Successful completion of this approach is expected to result in improved detection and treatment of micromets with reduced side effects. This is ultimately expected to lead to reduced recurrence rates and overall improved survival. Although this imaging approach focuses on epithelial ovarian cancer diagnosis and treatment, it can be applicable to a wide range of epithelial diseases, such as oral, lung, and gastrointestinal cancers.

项目摘要/摘要 晚期卵巢癌管理的主要挑战是传播 腹膜内腔内的微观肿瘤结节。尽管手术并调整化疗，但 多达50％的患者可以显示隐匿性传播疾病，只有43％的存活率。此外， 全身化疗可以具有有毒的副作用。那是最近旨在改善检测的努力 和处理微型的处理。化学疗法（CPT），化学疗法和光动力学的组合 治疗是一种新兴的癌症治疗方式，可以提供两种疗法的协同效率。 总体目标是为高级实施定量的腹腔镜成像和治疗方法 检测微型的检测和CPT的靶向破坏卵巢微型组的优化并减少 有毒的副作用。定量荧光腹腔镜成像将提供高灵敏度和分辨率 检测微型组以及图像指导的药物输送。叶酸受体α（FA）将用作 有希望的靶标，因为它高度特异性涉及上皮卵巢癌。提议的目标CPT 化合物的肿瘤特异性约为6倍，可增强荧光对比度。这些叶酸的目标， 卟啉 - 磷脂掺杂的脂质体直接由近红外（NIR）光触发。这激活了 抗癌光敏剂外层，并释放抗癌剂阿霉素（DOX）。同时 预计纳米载体将改善对生物组织中的微粒，组织滥用和散射的检测 混淆荧光对比。基于空间频域成像的定量成像可以 消除这些混杂效果并提供定量对比度以实现更敏感的检测 与原始荧光或白光可视化相比。此外，这种定量能力可以起作用 在近实时的时间内提供有关药物释放的反馈，从而允许图像引导的优化治疗 光以确保每个肿瘤中的全部药物释放。在AIM 1中，宽场双通道腹腔镜，快速 将实施和优化定量算法和靶向脂质体纳米构造。在AIM 2中， 该平台将在体内进行验证，以改善Micromets与原始荧光和白光的检测。 在AIM 3中，该平台的效率将在体内验证，以破坏目标肿瘤中的微粒 减少对周围正常组织的毒性。预计成功完成此方法将导致 改善了副作用减少的微型的检测和处理。最终期望这会导致 降低的复发率和总体上提高了生存率。尽管这种成像方法着重于上皮 卵巢癌的诊断和治疗，可以适用于多种上皮疾病，例如 口腔，肺和胃肠道癌。